@import tool.ReportPojo.ReportData
@import tool.ReportPojo.ReportInfo
@import views.user.report.IndexTool._
@(path: String, info: ReportInfo, resultPath: String)(implicit data: ReportData)

@getIPath3Index(i: Int) = @{
	val index = if(data.configDatas(i).isIPathExec) {
		1
	} else 0
	index
}

@getEnrich3Index(i: Int) = @{
	val index = if(data.configDatas(i).isEnrichExec) {
		1
	} else 0
	index + getIPath3Index(i)
}

@getPathway3Index(i: Int) = @{
	val index = if(data.configDatas(i).isPathwayExec) {
		1
	} else 0
	index + getEnrich3Index(i)
}

@getDiagnose2Index(i: Int) = @{
	val index = if(data.configDatas(i).isDiagnoseExec) {
		1
	} else 0
	index + getParCor2Index(i)
}

@getResultIndex = @{
	val index = if(data.outerData.hasQc) {
		1
	} else 0
	index + 2
}

@getSummaryIndex = @{
	getResultIndex + 1
}

@getIntroIndex = @{
	getSummaryIndex + 1
}

@getNewPageClass = @{
	if(info.isMet) "newPage" else ""
}

<style>

		.nav {
			color: green;
			font: 18px "微软雅黑";
			valign: middle;
			text-align: left;
			padding-left: 15px;
			border-top: 1px solid #eee;
		}

		.singleSep {
			margin-top: 25px;
			border-bottom: 1px dashed #262626;
		}

		.doubleSep {
			margin-top: 25px;
			height: 5px;
			border-bottom: 1px dashed #262626;
			border-top: 1px dashed #262626;
		}

		.myImg {
			width: 100%;
		}

		body {
			font-family: Times, times;
		}

</style>

<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN" >
<html>
	<head>
		<TITLE>代谢组分析结题报告 </TITLE>
		<META NAME="Modified" CONTENT="mengfanrui@@novogene.cn">
		<META NAME="Version" CONTENT="2014820v2.0">
		<meta charset="utf-8"/>
		<meta http-equiv="Content-Type" content="text/html; charset=utf-8" />
		<link rel="stylesheet" media="screen" href="@(path)/css/bootstrap.css">
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		<style media="print">
				.noprint {
					DISPLAY: none;
				}
		</style>
	</head>

	<body style="padding-top: 0em;
		padding-bottom: 0em">

		<div id="main" style="width: 95%;
			top: 100px;">
			@if(info.isMet) {
				@user.report.pdf.metHome(path, data, info)
			}


			<div id="page" class="@getNewPageClass">
				@user.report.pdf.pageHeader(path, data, info)
				<br />
				<h2 class="titleLevel1" id="2" ><span id="项目简介">1 Project Summary</span></h2>
				<p class="paragraph">
					The samples provided by the client were photographed, recorded and immediately stored at -80°C freezer(Forma 900 series, Thermo Fisher Scientific,Waltham, MA, USA). The group information about the samples is shown in the table below.
					<br>
					<br>
					Raw data stores in
					<a href="@(resultPath)Preprocessed_Data/00_AllMet_Raw.csv">00_AllMet_Raw.csv</a>
					<a href="@(resultPath)Preprocessed_Data" target="_blank"><span class="fa fa-folder-open"></span></a>
					<br>
					Cleaned data after pre-processing(Normalization, LOESS etc.) is stored in<a href="@(resultPath)Preprocessed_Data/04_AllMet.csv">
					04_AllMet.csv</a>
					<a href="@(resultPath)Preprocessed_Data" target="_blank"><span class="fa fa-folder-open"></span></a>
				</p>
				<div class="doubleSep"></div>
			</div>

			@if(data.outerData.hasQc) {
				<div id="page" class="newPage">
					@user.report.pdf.pageHeader(path, data, info)
					<br />

					<h2 class="titleLevel1" ><span id="质量控制">2 Quality Control</span></h2>
					<p class="paragraph">
						Quality control (QC) samples were obtained by mixing a small aliquot of each biological sample in the study set. The pooled QC represented both the sample matrix and metabolite composition of the samples. The raw pooled QC mixture were used to produce multiple QC samples that would be analyzed during the whole injection sequence. In metabolomics the application of QC samples provides a mechanism to evaluate the quality and assess the analytical variance of the aquired data.
					</p>


					<h3 id="qcBasic" class="myBasic titleLevel2"><span id="多变量质控图">1 Multivariate Control Chart</span></h3>
					<p class="paragraph">
						<b>Multivariate Control Chart (MCC)</b>
						is a powerful tool when there are more than one variables and some variables may be correlated. By using the score values of one principle component (t1, t2, etc.) from a multivariate model, herein Principal Component Analysis, as the y-variable, and injection sequence as the x variable, a MCC is constructed. Hence, MCC displays the collected data over time and can monitor variations introduced by a series of laboratory procedures.
					</p>
					<div class="noInNewPage">
						<p class="name_table">Figure 1 Multivariate Control Chart</p>
						<div align="center">
							<a id="example2" data-fancybox="gallery" href="@(resultPath)Quality_Control/01_PC1_with_All_Samples/PC1_Dotplot.png">
								<img class="wid2" src="@(resultPath)Quality_Control/01_PC1_with_All_Samples/PC1_Dotplot.png">
							</a>
						</div>
					</div>
					@user.reportEn.qc(resultPath)

				</div>
					<!----------------------------------------- QC样本间相关性 -------------------------------------->
				<div id="page" class="newPage">
					@user.report.pdf.pageHeader(path, data, info)
					<br />
					<h3 class="titleLevel2" id="QC样本间相关性">
						<span id="qc02" class="myMain">
							2 Correlation Between QC Samples
						</span>
					</h3>

					@user.reportEn.qc2(resultPath)

					<div class="noInNewPage">
						<p class="name_table">Figure 2 Correlation Coefficient Heatmap among QC samples</p>
						<div class="center">
							<a id="example2" data-fancybox="gallery" href="@(resultPath)Quality_Control/02_QC_Correlation_Pearson/QC_Pearson_Correlation_Heatmap.png">
								<img class="wid2" src="@(resultPath)Quality_Control/02_QC_Correlation_Pearson/QC_Pearson_Correlation_Heatmap.png" ></a>
						</div>
					</div>


				</div>

					<!----------------------------------------- 样本代谢轮廓变异 -------------------------------------->
				<div id="page" class="newPage">
					@user.report.pdf.pageHeader(path, data, info)
					<br />
					<h3 class="titleLevel2" id="样本代谢轮廓变异">
						<span id="qc03" class="myMain">
							3 Metabolic Profile Variation
						</span>
					</h3>

					<p class="paragraph">
						The overview principal component analysis (PCA) score plot is shown in Figure 3. All samples including QC samples are shown in the plot. Score plot with aggregated QC samples(QC samples gather together) indicates that the quality control is good and the detection process is stable. As an “Unsupervised Learning” method, PCA is helpful to find homogenous subgroups (clusters), and to find patterns (usually through dimensionality reduction) and outliers.
					</p>
					<div class="noInNewPage">
						<p class="name_table">　Figure 3 PCA Score plot</p>
						<p class="center">
							<a id="example2" data-fancybox="gallery" href="@(resultPath)Quality_Control/01_PC1_with_All_Samples/PCA_with_All_Samples_First2PCs.png">
								<img class="wid2" src="@(resultPath)Quality_Control/01_PC1_with_All_Samples/PCA_with_All_Samples_First2PCs.png" ></a>
						</p>
					</div>

				</div>

				<div id="page" class="newPage">
					@user.report.pdf.pageHeader(path, data, info)
					<br />

					<h3 class="titleLevel2" id="代谢物鉴定及注释情况">
						<span id="qc04" class="myMain"> 4 Metabolite Annotation and Classification</span>
					</h3>
					@user.reportEn.metAnno(resultPath, data)

					<div class="doubleSep"></div>

				</div>
			}

			<br />
			<div class="newPage">
			@user.report.pdf.pageHeader(path, data, info)
			</div>
			<h2 class="titleLevel1" ><span name="分析结果"> @(getResultIndex)、Results</span></h2>

			@for(i <- data.treats.indices) {

				<h4 id="@(data.treats(i))Basic" class="myMain myBasic titleLevel3">
					<span id="@(data.treats(i))代谢物分类总览" class="myLink">
						@(i + 1).1  @data.treats(i)
					</span>
				</h4>

				<div id="page">
					@user.reportEn.metClassify(resultPath, data, i)
				<div class="noInNewPage">
					<p class="name_table">　Figure @(i + 1)-1  Relative abundance of each metabolite class</p>
					<div class="row">
						<div class="col-sm-12">

							<div class="row">
								<div class="col-sm-6">
									<p class="imgP"><span>A</span></p>
									<img class="myImg" src="@(resultPath)Treatment/@(data.treats(i))/01_Basic_Statistics/Metabolite_Class_Statistics/Class_Barplot_by_Group.png"
									alt="A">
								</div>
								<div class="col-sm-6">
									<p class="imgP"><span>B</span></p>
									<img class="myImg" src="@(resultPath)Treatment/@(data.treats(i))/01_Basic_Statistics/Metabolite_Class_Statistics/Class_Barplot_by_Sample.png"
									alt="B">
								</div>
							</div>

						</div>
					</div>
				</div>

				</div>


				<div id="page" class="newPage">
					@user.report.pdf.pageHeader(path, data, info)

				<div class="row">
					<div class="col-sm-12">
						<h4 id="@(data.treats(i))Mul" class="myMain titleLevel3">
							<span id="@(data.treats(i))多维统计分析">
								@(i + 1).2 Multi-dimensional Statistics
							</span>
						</h4>
					</div>

				</div>

				<br />
				<h5 class="titleLevel4">@(i + 1).2.1 PCA </h5>
				<p class="paragraph">
					PCA 2D score plot and PCA 3D score plot are shown in Figure @(i + 1)-2
				</p>

				<p class="paragraph">
					PCA 2D score plot with sample names labeled is shown in
					<a href="@(resultPath)Treatment/@(data.treats(i))/02_PCA/All_Groups/PCA_Score_2D_Label.pdf" target="_blank">PCA_Score_2D_Label.pdf</a>
					<a href="@(resultPath)Treatment/@(data.treats(i))/02_PCA/All_Groups" target="_blank"><span class="fa fa-folder-open"></span></a>
				</p>
				<p class="paragraph">
					Pairwise PCA 2D score plots is shown in
					<a href="@(resultPath)Treatment/@(data.treats(i))/02_PCA/All_Groups/All_Combinaiton/All_PCs_Pairsplot.pdf" target="_blank">
					All_PCs_Pairsplot.pdf
					</a>
					<a href="@(resultPath)Treatment/@(data.treats(i))/02_PCA/All_Groups/All_Combinaiton" target="_blank"><span class="fa fa-folder-open"></span></a>
				</p>
				<div class="noInNewPage">
					<p class="name_table">Figure @(i + 1)-2 PCA Score Plot</p>

					<div class="row">
						<div class="col-sm-6">
							<p class="imgP"><span>A</span></p>
							<img class="myImg" src="@(resultPath)Treatment/@(data.treats(i))/02_PCA/All_Groups/PCA_Score_2D.png"
							alt="A">
						</div>
						<div class="col-sm-6">
							<p class="imgP"><span>B</span></p>
							<img class="myImg" src="@(resultPath)Treatment/@(data.treats(i))/02_PCA/All_Groups/PC123_Score_3D.png"
							alt="B">
						</div>
					</div>

				</div>


				<div class="row">
					<div class="col-sm-12">
						<p class="paragraph">
															Figure @(i + 1)-3 display s PCA 2D score plot and boxplot of first two principal component. PCA scores of each group are also displayed in the form of boxplot seperately, which can be helpful to show patterns between different groups especially when more than 3 groups are displayed in one single score plot.
						</p>
					</div>

				</div>

				<div class="noInNewPage">
					<p class="name_table">Figure @(i + 1)-3 PCA Score Plot With Principal Component Boxplot</p>
					<p class="center">
						<img class="wid2" src="@(resultPath)Treatment/@(data.treats(i))/02_PCA/All_Groups/PCA_Score_with_Boxplot_with_Points.png" />
					</p>

				</div>

				<p class="paragraph">
						PCA score plots of each single group are stored in file folder
					<a target="_blank" href="@(resultPath)Treatment/@(data.treats(i))/02_PCA/Uni_Group">Uni_Group</a>
							. After blocking inter-group variance, these plots can throw light on the intra-group variance and find out potential outliers.
				</p>
				</div>

				<div id="page" class="newPage">
					@user.report.pdf.pageHeader(path, data, info)
				<br />
				<h5 class="titleLevel4">@(i + 1).2.2 PLS-DA Analysis</h5>
				<p class="paragraph">
					PLS-DA scores are shown in
					<a href="@(resultPath)Treatment/@(data.treats(i))/03_PLS_DA/PLSDA_Score.csv">PLSDA_Score.csv</a>
					<a href="@(resultPath)Treatment/@(data.treats(i))/03_PLS_DA" target="_blank"><span class="fa fa-folder-open"></span></a>
				</p>
				<p class="paragraph">
					PLS-DA 2D score plot is shown in
					<a href="@(resultPath)Treatment/@(data.treats(i))/03_PLS_DA/PLSDA_Score_2D.pdf" target="_blank">PLSDA_Score_2D.pdf</a>
					<a href="@(resultPath)Treatment/@(data.treats(i))/03_PLS_DA" target="_blank"><span class="fa fa-folder-open"></span></a>
				</p>
				<p class="paragraph">
					PLS-DA 2D score plot with sample names labeled is shown in
					<a href="@(resultPath)Treatment/@(data.treats(i))/03_PLS_DA/PLSDA_Score_2D_Label.pdf" target="_blank">PLSDA_Score_2D_Label.pdf</a>
					<a href="@(resultPath)Treatment/@(data.treats(i))/03_PLS_DA" target="_blank"><span class="fa fa-folder-open"></span></a>
				</p>
				<p class="paragraph">
					PLS-DA 2D score plot with principal component boxplot is shown in
					<a href="@(resultPath)Treatment/@(data.treats(i))/03_PLS_DA/PLSDA_Score_with_Boxplot_with_Points.pdf" target="_blank">
					PLSDA_Score_with_Boxplot_with_Points.pdf
					</a>
					<a href="@(resultPath)Treatment/@(data.treats(i))/03_PLS_DA" target="_blank"><span class="fa fa-folder-open"></span></a>
				</p>

				</div>

				@if(!data.configDatas(i).isMul) {
					<div id="page" class="newPage">
						@user.report.pdf.pageHeader(path, data, info)
						<br />
						<h5 class="titleLevel4">@(i + 1).2.3 OPLS-DA Analysis</h5>

						<p class="paragraph">
							OPLS-DA 2D score plot is shown in Figure @(i + 1)-4 A
						</p>
						<p class="paragraph">
							Permutation test result is shown in Figure @(i + 1)-4 B
						</p>
						<p class="paragraph">
							OPLS-DA scores are shown in
							<a href="@(resultPath)Treatment/@(data.treats(i))/04_OPLS_DA/OPLSDA_Score.csv">
								OPLSDA_Score.csv</a>
							<a href="@(resultPath)Treatment/@(data.treats(i))/04_OPLS_DA" target="_blank"><span class="fa fa-folder-open"></span></a>
						</p>
						<p class="paragraph">
							OPLS-DA 2D score plot with sample names labeled is shown in
							<a href="@(resultPath)Treatment/@(data.treats(i))/04_OPLS_DA/OPLSDA_Score_2D_Label.pdf" target="_blank">
								OPLSDA_Score_2D_Label.pdf
							</a>
							<a href="@(resultPath)Treatment/@(data.treats(i))/04_OPLS_DA" target="_blank"><span class="fa fa-folder-open"></span></a>
						</p>
						<div class="noInNewPage">
							<p class="name_table">Figure @(i + 1)-4 OPLS-DA Score Plot and Permutation Plot</p>
							<div class="row">
								<div class="col-sm-6">
									<p class="imgP"><span>A</span></p>
									<img class="myImg" src="@(resultPath)Treatment/@(data.treats(i))/04_OPLS_DA/OPLSDA_Score_2D.png"
									alt="A">
								</div>
								<div class="col-sm-6">
									<p class="imgP"><span>B</span></p>
									<img class="myImg" src="@(resultPath)Treatment/@(data.treats(i))/04_OPLS_DA/Model_Validation/OPLSDA_Permutation.png"
									alt="B">
								</div>
							</div>
						</div>


					</div>

					<div id="page" class="newPage">
						@user.report.pdf.pageHeader(path, data, info)
						<br />
						<div class="row">
							<div class="col-sm-12">
								<h5 class="titleLevel4">@(i + 1).2.4 Differential Metabolites Selection -- Multi-Dimensional Statistics</h5>
							</div>
						</div>

						@user.reportEn.oplsda(resultPath)
						<p class="paragraph">
							VIP and Corr.Coeffs data of metabolites is shown in
							<a href="@(resultPath)Treatment/@(data.treats(i))/04_OPLS_DA/OPLSDA_VIP.csv">
								OPLSDA_VIP.csv</a>
							<a href="@(resultPath)Treatment/@(data.treats(i))/04_OPLS_DA" target="_blank"><span class="fa fa-folder-open"></span></a>
						</p>
						<p class="paragraph">
							Volcano Plot of OPLS-DA model is shown in Figure @(i + 1)-5
						</p>
						<div class="noInNewPage">
							<p class="name_table">Figure @(i + 1)-5 Volcano Plot of OPLS-DA model</p>
							<p class="center">
								<img class="wid2" src="@(resultPath)Treatment/@(data.treats(i))/04_OPLS_DA/OPLSDA_VPlot.png" />
							</p>
						</div>


					</div>

				}

				<div id="page" class="newPage">
					@user.report.pdf.pageHeader(path, data, info)

				<h4 id="@(data.treats(i))Single" class="myMain titleLevel3">
					<span id="@(data.treats(i))单维统计分析">
						@(i + 1).3 Univariate Statistics
					</span>
				</h4>

				<br />
				<h5 class="titleLevel4">@(i + 1).3.1 Metabolites Z-Score Plot</h5>
				<p class="paragraph">
					Z-Score data of metabolites is shown in
					<a href="@(resultPath)Treatment/@(data.treats(i))/01_Basic_Statistics/Z_Score.csv">Z_Score.csv</a>
					<a href="@(resultPath)Treatment/@(data.treats(i))/01_Basic_Statistics" target="_blank"><span class="fa fa-folder-open"></span></a>
				</p>
				<p class="paragraph">
					Z-Score Plot is shown in
					<a href="@(resultPath)Treatment/@(data.treats(i))/01_Basic_Statistics/Z_Score_Heatmap.pdf" target="_blank">Z_Score_Plot.pdf</a>
					<a href="@(resultPath)Treatment/@(data.treats(i))/01_Basic_Statistics" target="_blank"><span class="fa fa-folder-open"></span></a>
				</p>
				</div>

				@if(data.configDatas(i).groups.size == 2) {
					<div id="page" class="newPage">
						@user.report.pdf.pageHeader(path, data, info)
						<br />
						<h5 class="titleLevel4">@(i + 1).3.2 Differential Metabolites Selection – Univariate Statistics</h5>
						<p class="paragraph">
							The differential metabolites can also be obtained using univariate statistical analysis (student T-test or Mann-Whitney U test, depending on the normality of data and homogeneity of variance), especially when the multivariate OPLS-DA model fails to build reliable discriminant model under some conditions (i.e. non-homogeneousclasses or large intra-class variability).
						</p>
						<p class="paragraph">
							Volcano Plot of Univariate Statistics is shown in Figure @(i + 1)-6
						</p>
						@user.reportEn.singleStat(resultPath, data, i)
					</div>
				} else {
					@* 多组差异代谢物筛选*@
					<div id="page" class="newPage">
						@user.report.pdf.pageHeader(path, data, info)
						<br />
						<h5 class="titleLevel4">@(i + 1).3.2 Differential Metabolites Selection – Univariate Statistics</h5>
						<p class="paragraph">
							The differential metabolites can be also obtained using univariate statistical analysis (Anova or Kruskal-Wallis test, depending on the normality of data and homogeneity of variance)
						</p>
						<p class="paragraph">
							In this project, threshold value for differential metabolites selection is: P < @(data.configDatas(i).pValue)
						</p>
						<p class="paragraph">
							P value, basic information and FC of the differential metabolites are shown in
							<a href="@(resultPath)Treatment/@(data.treats(i))/@(data.resultDatas(i).uniDir)/AllMet_Test.csv">
								AllMet_Test.csv
							</a>
							<a href="@(resultPath)Treatment/@(data.treats(i))/@(data.resultDatas(i).uniDir)" target="_blank"><span class="fa fa-folder-open"></span></a>
						</p>
						<p class="paragraph">
							Z Score dot plot of the differential metabolites is shown in
							<a href="@(resultPath)Treatment/@(data.treats(i))/@(data.resultDatas(i).uniDir)/Z_Score_Plot.pdf" target="_blank">
								Z_Score_Plot.pdf
							</a>
							<a href="@(resultPath)Treatment/@(data.treats(i))/@(data.resultDatas(i).uniDir)" target="_blank"><span class="fa fa-folder-open"></span></a>
						</p>
						<p class="paragraph">
							Boxplot of top 9 differential metabolites ordered by P value are shown in Figure @(i + 1)-4
						</p>
						<p class="paragraph">
							Boxplot of all differential metabolites are shown in
							<a href="@(resultPath)Treatment/@(data.treats(i))/@(data.resultDatas(i).uniDir)/AllMet_Boxplot.pdf" target="_blank">
								AllMet_Boxplot.pdf
							</a>
							<a href="@(resultPath)Treatment/@(data.treats(i))/@(data.resultDatas(i).uniDir)" target="_blank"><span class="fa fa-folder-open"></span></a>
						</p>
						<p class="paragraph">
							Box-scatter plot of all differential metabolites are shown in
							<a href="@(resultPath)Treatment/@(data.treats(i))/@(data.resultDatas(i).uniDir)/AllMet_Boxplot_with_Points.pdf" target="_blank">
								AllMet_Boxplot_with_Points.pdf
							</a>
							<a href="@(resultPath)Treatment/@(data.treats(i))/@(data.resultDatas(i).uniDir)" target="_blank"><span class="fa fa-folder-open"></span></a>
						</p>
						<p class="paragraph">
							Violin plot of all differential metabolites are shown in
							<a href="@(resultPath)Treatment/@(data.treats(i))/@(data.resultDatas(i).uniDir)/AllMet_Vioplot.pdf" target="_blank">
								AllMet_Vioplot.pdf
							</a>
							<a href="@(resultPath)Treatment/@(data.treats(i))/@(data.resultDatas(i).uniDir)" target="_blank"><span class="fa fa-folder-open"></span></a>
						</p>

						<div class="noInNewPage">
							<p class="name_table">
								Figure @(i + 1)-4 Boxplot of Differential Metabolites based on Univariate Statistics
							</p>
							<p class="center">
								<img class="wid2" src="@(resultPath)Treatment/@(data.treats(i))/@(data.resultDatas(i).uniDir)/AllMet_Boxplot.png" />
							</p>
						</div>

					</div>
				}

				<div id="page" class="newPage">
					@user.report.pdf.pageHeader(path, data, info)

				<h4 id="@(data.treats(i))Biomarker" class="myMain titleLevel3">
					<span id="@(data.treats(i))潜在生物标志物筛选">
						@(i + 1).4 Potential Biomarker Selection
					</span>
				</h4>

				<br />
					@user.reportEn.biomarker(resultPath, data, i)
					@if(data.configDatas(i).isMul) {
						<p class="paragraph">
							OPLS-DA analysis isn’t avaliable in this treat because more than two groups are presented in this treat. Thus, potential biomarkers is the same as differential metabolites obtained in “Differential Metabolites Selection – Univariate Statistics”.
						</p>
					} else {
						<p class="paragraph">
							Venn Plot of differential metabolites from multi-dimensional statistics and univariate statistics is shown in Figure @(i + 1)-@getPotentialImageIndex(i)
						</p>
						<div class="noInNewPage">
							<p class="name_table">
								Figure @(i + 1)-@getPotentialImageIndex(i) Venn Plot of differential metabolites
							</p>
							<p class="center">
								<img class="wid2" src="@(resultPath)Treatment/@(data.treats(i))/@(data.resultDatas(i).potentialDir)/Venn_Plot.png"/>
							</p>
						</div>

					}

				</div>

				<div id="page" class="newPage">
					@user.report.pdf.pageHeader(path, data, info)
				<br />
				<h5 class="titleLevel4">@(i + 1).4.1  Potential Biomarkers</h5>

					@if(data.resultDatas(i).markers.rows.size != 0) {
						<p class="paragraph">
							Potential biomarkers is also shown in Table @(i + 1)-1
						</p>
						<p class="paragraph">
							Boxplot of potential biomarkers is shown in
							<a href="@(resultPath)Treatment/@(data.treats(i))/@(data.resultDatas(i).potentialDir)/Markers_Boxplot_with_Points.pdf" target="_blank">
								Markers_Boxplot.pdf
							</a>
							<a href="@(resultPath)Treatment/@(data.treats(i))/@(data.resultDatas(i).potentialDir)" target="_blank"><span class="fa fa-folder-open"></span></a>
						</p>
						<p class="paragraph">
							Violin plot of potential biomarkers is shown in
							<a href="@(resultPath)Treatment/@(data.treats(i))/@(data.resultDatas(i).potentialDir)/Markers_Vioplot.pdf" target="_blank">
								Markers_Vioplot.pdf
							</a>
							<a href="@(resultPath)Treatment/@(data.treats(i))/@(data.resultDatas(i).potentialDir)" target="_blank"><span class="fa fa-folder-open"></span></a>
						</p>
						<p class="paragraph">
							Z Score plot of potential biomarkers is shown in
							<a href="@(resultPath)Treatment/@(data.treats(i))/@(data.resultDatas(i).potentialDir)/Markers_Z_Score_Plot.pdf" target="_blank">
								Markers_Z_Score_Plot.pdf
							</a>
							<a href="@(resultPath)Treatment/@(data.treats(i))/@(data.resultDatas(i).potentialDir)" target="_blank"><span class="fa fa-folder-open"></span></a>
						</p>
					} else {
						@user.reportEn.html.noResult()
					}

				</div>

				@if(data.configDatas(i).isIPathExec || data.configDatas(i).isEnrichExec || data.configDatas(i).isPathwayExec) {
					<div class="newPage">
					@user.report.pdf.pageHeader(path, data, info)
					</div>

					<h4 id="@(data.treats(i))Pathway" class="myMain titleLevel3">
						<span id="@(data.treats(i))通路分析">
							@(i + 1).@(getPathway2Index(i)) Pathway Analysis
						</span>
					</h4>

					@if(data.resultDatas(i).markers.rows.nonEmpty) {
						<p class="paragraph">
						@user.reportEn.modelDiff(resultPath, data, i)
						</p>

						@if(data.configDatas(i).isIPathExec) {
							<div id="page">
								<br/>
								<h5 class="titleLevel4">@(i + 1).@(getPathway2Index(i)).1 iPath Pathway Analysis</h5>
								@user.reportEn.iPath(resultPath, i)
								<div class="noInNewPage">
									<p class="name_table">Figure @(i + 1)-@getIPathImageIndex(i) iPathway Network Plot</p>
									<p class="center">
										<img class="wid2" src="@(resultPath)Treatment/@(data.treats(i))/@(data.resultDatas(i).pathwayDir)/iPath3/iPath3.png"/>
									</p>
								</div>

							</div>
						}

						@if(data.configDatas(i).isEnrichExec) {
							<div id="page" class="newPage">
								@user.report.pdf.pageHeader(path, data, info)
								<br />
								<h5 class="titleLevel4">@(i + 1).
									@(getPathway2Index(i)).@(getEnrich3Index(i)) Pathway Enrichment Analysis
								</h5>
								@for(j <- data.configDatas(i).libTypes.indices) {
									@if(j > 0) {
										<div class="newPage">
										@user.report.pdf.pageHeader(path, data, info)
										</div>
									}
									<h6 class="titleLevel5">
										@(i + 1).
										5.@(getEnrich3Index(i)).@(j + 1) Pathway Enrichment Analysis by Pathway-associated metabolite sets (@data.configDatas(i).libTypes(j))
									</h6>
									<p class="paragraph">
												Pathway enrichment analysis using Pathway-associated metabolite sets (@data.configDatas(i).libTypes(j)) is shown in Figure @(i + 1)-@getEnrichImageIndex(i, j).
									</p>
									@user.reportEn.enrich(resultPath, i, j)

								}
							</div>
						}

						@if(data.configDatas(i).isPathwayExec) {
							<div id="page" class="newPage">
								@user.report.pdf.pageHeader(path, data, info)
								<br/>
								<h5 class="titleLevel4">@(i + 1).
									@(getPathway2Index(i)).@(getPathway3Index(i)) Pathway Analysis
								<h6 class="titleLevel5">
									@(i + 1).
									@(getPathway2Index(i)).
									@(getPathway3Index(i)).1 Pathway Analysis by @(data.configDatas(i).species) set
								</h6>
								<p class="paragraph">
									Detailed Pathway Analysis result by @(data.configDatas(i).species) set is shown in
									<a href="@(resultPath)Treatment/@(data.treats(i))/@(data.resultDatas(i).pathwayDir)/Pathway_Analysis/Pathway_Result.csv">
										Pathway_Result.csv
									</a>
									<a href="@(resultPath)Treatment/@(data.treats(i))/@(data.resultDatas(i).pathwayDir)/Pathway_Analysis" target="_blank"><span class="fa fa-folder-open"></span></a>

								</p>
								<p class="paragraph">
									Pathway Analysis bar plot by @(data.configDatas(i).species) set is shown in
									<a href="@(resultPath)Treatment/@(data.treats(i))/@(data.resultDatas(i).pathwayDir)/Pathway_Analysis/Pathway_Barplot.pdf" target="_blank">
										Pathway_Barplot.pdf
									</a>
									<a href="@(resultPath)Treatment/@(data.treats(i))/@(data.resultDatas(i).pathwayDir)/Pathway_Analysis" target="_blank"><span class="fa fa-folder-open"></span></a>

								</p>
								@if(data.resultDatas(i).hasBubble) {
									<p class="paragraph">
										Pathway Analysis bubble plot by @(data.configDatas(i).species) set is shown in Figure @(i + 1)-@(getPathwayImageIndex(i))
									</p>
								}
								@user.reportEn.pathway(resultPath, i)

								@if(data.resultDatas(i).hasBubble) {
									<div class="noInNewPage">
										<p class="name_table">
											Figure @(i + 1)-@(getPathwayImageIndex(i)) Pathway Analysis Bubble Plot by @(data.configDatas(i).species) set
										</p>
										<p class="center">
											<img class="wid2" src="@(resultPath)Treatment/@(data.treats(i))/@(data.resultDatas(i).pathwayDir)/Pathway_Analysis/Pathway_Bubbleplot.png"/>
										</p>
									</div>
								}

							</div>
						}
					} else {
						@user.reportEn.html.noResult()
					}


				}

				@if(data.configDatas(i).isSelfCor || data.configDatas(i).isCor || data.configDatas(i).isParCor) {
					<div class="newPage">
					@user.report.pdf.pageHeader(path, data, info)
					</div>
					<h4 id="@(data.treats(i))Cor" class="myMain titleLevel3">
						<span id="@(data.treats(i))Spearman相关性分析">
							@(i + 1).@(getCor2Index(i)) Spearman Correlation Analysis
						</span>
					</h4>

					@if(data.resultDatas(i).markers.rows.nonEmpty) {
						<div id="page">
							<br />
							<p class="paragraph">
							@user.reportEn.modelDiff(resultPath, data, i)
							</p>
							@user.reportEn.selfCor(resultPath, i)
						</div>

						@if(data.configDatas(i).isCor) {
							@for(j <- data.outerData.extraDatas.indices) {
								<div id="page" class="newPage">
									@user.report.pdf.pageHeader(path, data, info)
								<br />
								<h5 class="titleLevel4">@(i + 1).
									@(getCor2Index(i)).@(j + 2) Inter Correlation Analysis with Data from @(data.outerData.extraDatas(j))
								</h5>
									@user.reportEn.uploadCor(resultPath, i, j)
								</div>
							}
						}

						@if(data.configDatas(i).isParCor) {

							<div id="page" class="newPage">
								@user.report.pdf.pageHeader(path, data, info)

								<h4 id="@(data.treats(i))ParCor" class="myMain titleLevel3">
									<span id="@(data.treats(i))偏相关分析">
										@(i + 1).@(getParCor2Index(i)) Partial Correlation Analysis
									</span>
								</h4>

								<br />
								<p class="paragraph">
								@user.reportEn.modelDiff(resultPath, data, i)
								</p>

								@user.reportEn.parCor(resultPath, i)

							</div>

						}

					} else {
						@user.reportEn.html.noResult()
					}
				}

				@if(data.configDatas(i).isDiagnoseExec) {

					<div class="newPage">
					@user.report.pdf.pageHeader(path, data, info)
					</div>
					<h4 id="@(data.treats(i))Diagnose" class="myMain titleLevel3">
						<span id="@(data.treats(i))诊断结果">
							@(i + 1).@(getDiagnose2Index(i)) Prediction and Diagnosis Model
						</span>
					</h4>

					@if(data.resultDatas(i).markers.rows.nonEmpty) {

						<div id="page">
							<br/>
							<p class="paragraph">
							@user.reportEn.modelDiff(resultPath, data, i)
							</p>
							@user.reportEn.diagnoseResult(resultPath, i)
							<div class="newPage">
							@user.report.pdf.pageHeader(path, data, info)
							</div>
							<h5 class="titleLevel4">@(i + 1).@(getDiagnose2Index(i)).1 Feture Selection by RF</h5>
							<p class="paragraph">
								Importance scores of top 10 important differential metabolites by RF is stored in
								<a href="@(resultPath)Treatment/@(data.treats(i))/@(data.resultDatas(i).diagnoseDir)/01_Random_Forest/RF_Top@{data.configDatas(i).rfTop}_Imp_Rank.csv">
									RF_Top@{data.configDatas(i).rfTop}_Imp_Rank.csv
								</a>
								<a href="@(resultPath)Treatment/@(data.treats(i))/@(data.resultDatas(i).diagnoseDir)/01_Random_Forest" target="_blank"><span class="fa fa-folder-open"></span></a>
							</p>
							<p class="paragraph">
								Importance score plot of top 10 important differential metabolites by RF is shown in Figure
								@(i + 1)-@getDiagnoseImageIndex(i, 0)
							</p>
							<p class="paragraph">
								Importance scores of all differential metabolites by RF is stored in
								<a href="@(resultPath)Treatment/@(data.treats(i))/@(data.resultDatas(i).diagnoseDir)/01_Random_Forest/RF_Imp_Rank.csv">
									RF_Imp_Rank.csv
								</a>
								<a href="@(resultPath)Treatment/@(data.treats(i))/@(data.resultDatas(i).diagnoseDir)/01_Random_Forest" target="_blank"><span class="fa fa-folder-open"></span></a>
							</p>
							<p class="paragraph">
								Importance score plot of all differential metabolites by RF is shown in
								<a href="@(resultPath)Treatment/@(data.treats(i))/@(data.resultDatas(i).diagnoseDir)/01_Random_Forest/RF_Imp.pdf" target="_blank">
									RF_Imp.pdf
								</a>
								<a href="@(resultPath)Treatment/@(data.treats(i))/@(data.resultDatas(i).diagnoseDir)/01_Random_Forest" target="_blank"><span class="fa fa-folder-open"></span></a>
							</p>
							<div class="noInNewPage">
								<p class="name_table">
									Figure @(i + 1)-@getDiagnoseImageIndex(i, 0) Importance score plot by RF
								</p>
								<p class="center">
									<img class="wid2" src="@(resultPath)Treatment/@(data.treats(i))/@(data.resultDatas(i).diagnoseDir)/01_Random_Forest/RF_Top@{data.configDatas(i).rfTop}_Imp.png"/>
								</p>
							</div>
						</div>

						@if(!data.configDatas(i).isMul) {
							<div id="page" class="newPage">
								@user.report.pdf.pageHeader(path, data, info)
								<br/>
								<h5 class="titleLevel5">@(i + 1).@(getDiagnose2Index(i)).1.1 Logistic Regression</h5>
								<p class="paragraph">
									Results of Logistic Regression Model are shown below:
								</p>
								<p class="paragraph">
									Results of modeling are shown in file folder
									<a target="_blank" href="@(resultPath)Treatment/@(data.treats(i))/@(data.resultDatas(i).diagnoseDir)/01_Random_Forest/Diagnose_Model_Generation/Logistic_Regression">
										Logistic_Regression
									</a>
								</p>
								<p class="paragraph">
									Prediction result for each sample is shown in
									<a href="@(resultPath)Treatment/@(data.treats(i))/@(data.resultDatas(i).diagnoseDir)/01_Random_Forest/Diagnose_Model_Generation/Logistic_Regression/LR_Prediction.csv">
										LR_Prediction.csv
									</a>
									<a href="@(resultPath)Treatment/@(data.treats(i))/@(data.resultDatas(i).diagnoseDir)/01_Random_Forest/Diagnose_Model_Generation/Logistic_Regression" target="_blank"><span class="fa fa-folder-open"></span></a>
								</p>
								<p class="paragraph">
									Importance of each metabolite in model is shown in
									<a href="@(resultPath)Treatment/@(data.treats(i))/@(data.resultDatas(i).diagnoseDir)/01_Random_Forest/Diagnose_Model_Generation/Logistic_Regression/LR_VarImp.csv">
										LR_VarImp.csv
									</a>
									<a href="@(resultPath)Treatment/@(data.treats(i))/@(data.resultDatas(i).diagnoseDir)/01_Random_Forest/Diagnose_Model_Generation/Logistic_Regression" target="_blank"><span class="fa fa-folder-open"></span></a>
								</p>
								<p class="paragraph">
									ROC plot is shown in
									<a href="@(resultPath)Treatment/@(data.treats(i))/@(data.resultDatas(i).diagnoseDir)/01_Random_Forest/Diagnose_Model_Generation/Logistic_Regression/ROC_Curve.pdf" target="_blank">
										ROC_Curve.pdf
									</a>
									<a href="@(resultPath)Treatment/@(data.treats(i))/@(data.resultDatas(i).diagnoseDir)/01_Random_Forest/Diagnose_Model_Generation/Logistic_Regression" target="_blank"><span class="fa fa-folder-open"></span></a>
								</p>
								<p class="paragraph">
									PR curve is shown in
									<a href="@(resultPath)Treatment/@(data.treats(i))/@(data.resultDatas(i).diagnoseDir)/01_Random_Forest/Diagnose_Model_Generation/Logistic_Regression/PR_Curve.pdf" target="_blank">
										PR_Curve.pdf
									</a>
									<a href="@(resultPath)Treatment/@(data.treats(i))/@(data.resultDatas(i).diagnoseDir)/01_Random_Forest/Diagnose_Model_Generation/Logistic_Regression" target="_blank"><span class="fa fa-folder-open"></span></a>
								</p>
							</div>

							<div id="page" class="newPage">
								@user.report.pdf.pageHeader(path, data, info)
								<br/>
								<h5 class="titleLevel5">@(i + 1).@(getDiagnose2Index(i)).1.2 Random Forest</h5>
								<p class="paragraph">
									Results of Random Forest Model are shown below:
								</p>
								<p class="paragraph">
									Results of modeling are shown in file folder
									<a target="_blank" href="@(resultPath)Treatment/@(data.treats(i))/@(data.resultDatas(i).diagnoseDir)/01_Random_Forest/Diagnose_Model_Generation/Random_Forest">
										Random_Forest
									</a>
								</p>
								<p class="paragraph">
									Prediction result for each sample is shown in
									<a href="@(resultPath)Treatment/@(data.treats(i))/@(data.resultDatas(i).diagnoseDir)/01_Random_Forest/Diagnose_Model_Generation/Random_Forest/RF_Prediction.csv">
										RF_Prediction.csv
									</a>
									<a href="@(resultPath)Treatment/@(data.treats(i))/@(data.resultDatas(i).diagnoseDir)/01_Random_Forest/Diagnose_Model_Generation/Random_Forest" target="_blank"><span class="fa fa-folder-open"></span></a>

								</p>
								<p class="paragraph">
									Importance of each metabolite in model is shown in
									<a href="@(resultPath)Treatment/@(data.treats(i))/@(data.resultDatas(i).diagnoseDir)/01_Random_Forest/Diagnose_Model_Generation/Random_Forest/RF_VarImp.csv">
										RF_VarImp.csv
									</a>
									<a href="@(resultPath)Treatment/@(data.treats(i))/@(data.resultDatas(i).diagnoseDir)/01_Random_Forest/Diagnose_Model_Generation/Random_Forest" target="_blank"><span class="fa fa-folder-open"></span></a>
								</p>
								<p class="paragraph">
									ROC plot is shown in
									<a href="@(resultPath)Treatment/@(data.treats(i))/@(data.resultDatas(i).diagnoseDir)/01_Random_Forest/Diagnose_Model_Generation/Random_Forest/ROC_Curve.pdf" target="_blank">
										ROC_Curve.pdf
									</a>
									<a href="@(resultPath)Treatment/@(data.treats(i))/@(data.resultDatas(i).diagnoseDir)/01_Random_Forest/Diagnose_Model_Generation/Random_Forest" target="_blank"><span class="fa fa-folder-open"></span></a>

								</p>
								<p class="paragraph">
									PR curve is shown in
									<a href="@(resultPath)Treatment/@(data.treats(i))/@(data.resultDatas(i).diagnoseDir)/01_Random_Forest/Diagnose_Model_Generation/Random_Forest/PR_Curve.pdf" target="_blank">
										PR_Curve.pdf
									</a>
									<a href="@(resultPath)Treatment/@(data.treats(i))/@(data.resultDatas(i).diagnoseDir)/01_Random_Forest/Diagnose_Model_Generation/Random_Forest" target="_blank"><span class="fa fa-folder-open"></span></a>
								</p>
							</div>

							<div id="page" class="newPage">
								@user.report.pdf.pageHeader(path, data, info)
								<br/>
								<h5 class="titleLevel5">@(i + 1).@(getDiagnose2Index(i)).1.3 Gradient Boosting</h5>

								<p class="paragraph">
									Results of Gradient Boosting Model are shown below:
								</p>
								<p class="paragraph">
									Results of modeling are shown in file folder
									<a target="_blank" href="@(resultPath)Treatment/@(data.treats(i))/@(data.resultDatas(i).diagnoseDir)/01_Random_Forest/Diagnose_Model_Generation/Gradient_Boosting">
										Gradient_Boosting
									</a>
								</p>
								<p class="paragraph">
									Prediction result for each sample is shown in
									<a href="@(resultPath)Treatment/@(data.treats(i))/@(data.resultDatas(i).diagnoseDir)/01_Random_Forest/Diagnose_Model_Generation/Gradient_Boosting/GB_Prediction.csv">
										GB_Prediction.csv
									</a>
									<a href="@(resultPath)Treatment/@(data.treats(i))/@(data.resultDatas(i).diagnoseDir)/01_Random_Forest/Diagnose_Model_Generation/Gradient_Boosting" target="_blank"><span class="fa fa-folder-open"></span></a>
								</p>
								<p class="paragraph">
									Importance of each metabolite in model is shown in
									<a href="@(resultPath)Treatment/@(data.treats(i))/@(data.resultDatas(i).diagnoseDir)/01_Random_Forest/Diagnose_Model_Generation/Gradient_Boosting/GB_VarImp.csv">
										GB_VarImp.csv
									</a>
									<a href="@(resultPath)Treatment/@(data.treats(i))/@(data.resultDatas(i).diagnoseDir)/01_Random_Forest/Diagnose_Model_Generation/Gradient_Boosting" target="_blank"><span class="fa fa-folder-open"></span></a>
								</p>
								<p class="paragraph">
									ROC plot is shown in
									<a href="@(resultPath)Treatment/@(data.treats(i))/@(data.resultDatas(i).diagnoseDir)/01_Random_Forest/Diagnose_Model_Generation/Gradient_Boosting/ROC_Curve.pdf" target="_blank">
										ROC_Curve.pdf
									</a>
									<a href="@(resultPath)Treatment/@(data.treats(i))/@(data.resultDatas(i).diagnoseDir)/01_Random_Forest/Diagnose_Model_Generation/Gradient_Boosting" target="_blank"><span class="fa fa-folder-open"></span></a>
								</p>
								<p class="paragraph">
									PR curve is shown in
									<a href="@(resultPath)Treatment/@(data.treats(i))/@(data.resultDatas(i).diagnoseDir)/01_Random_Forest/Diagnose_Model_Generation/Gradient_Boosting/PR_Curve.pdf" target="_blank">
										PR_Curve.pdf
									</a>
									<a href="@(resultPath)Treatment/@(data.treats(i))/@(data.resultDatas(i).diagnoseDir)/01_Random_Forest/Diagnose_Model_Generation/Gradient_Boosting" target="_blank"><span class="fa fa-folder-open"></span></a>
								</p>
							</div>

						} else {
							@user.reportEn.html.noResult()
						}

						<div id="page" class="newPage">
							@user.report.pdf.pageHeader(path, data, info)
							<br/>
							<h5 class="titleLevel4">@(i + 1).@(getDiagnose2Index(i)).2 Feture Selection by SVM</h5>
							<p class="paragraph">
								Importance scores of top 10 important differential metabolites by SVM is stored in
								<a href="@(resultPath)Treatment/@(data.treats(i))/@(data.resultDatas(i).diagnoseDir)/02_Support_Vector_Machine/SVM_Top@{data.configDatas(i).svmTop}_Imp_Rank.csv">
									SVM_Top@{data.configDatas(i).svmTop}_Imp_Rank.csv
								</a>
								<a href="@(resultPath)Treatment/@(data.treats(i))/@(data.resultDatas(i).diagnoseDir)/02_Support_Vector_Machine" target="_blank"><span class="fa fa-folder-open"></span></a>
							</p>
							<p class="paragraph">
								Importance score plot of top 10 important differential metabolites by SVM is shown in Figure @(i + 1)-@getDiagnoseImageIndex(i, 1)
							</p>
							<p class="paragraph">
								Importance scores of all differential metabolites by SVM is stored in
								<a href="@(resultPath)Treatment/@(data.treats(i))/@(data.resultDatas(i).diagnoseDir)/02_Support_Vector_Machine/SVM_Imp_Rank.csv">
									SVM_Imp_Rank.csv
								</a>
								<a href="@(resultPath)Treatment/@(data.treats(i))/@(data.resultDatas(i).diagnoseDir)/02_Support_Vector_Machine" target="_blank"><span class="fa fa-folder-open"></span></a>
							</p>
							<p class="paragraph">
								Importance score of all differential metabolites by SVM is shown in
								<a href="@(resultPath)Treatment/@(data.treats(i))/@(data.resultDatas(i).diagnoseDir)/02_Support_Vector_Machine/SVM_Imp.pdf" target="_blank">
									SVM_Imp.pdf
								</a>
								<a href="@(resultPath)Treatment/@(data.treats(i))/@(data.resultDatas(i).diagnoseDir)/02_Support_Vector_Machine" target="_blank"><span class="fa fa-folder-open"></span></a>
							</p>

							<div class="noInNewPage">
								<p class="name_table">
									Figure  @(i + 1)-@getDiagnoseImageIndex(i, 1) Importance score plot by SVM
								</p>
								<p class="center">
									<img class="wid2" src="@(resultPath)Treatment/@(data.treats(i))/@(data.resultDatas(i).diagnoseDir)/02_Support_Vector_Machine/SVM_Top@{data.configDatas(i).svmTop}_Imp.png"/>
								</p>
							</div>
						</div>

						@if(!data.configDatas(i).isMul) {
							<div id="page" class="newPage">
								@user.report.pdf.pageHeader(path, data, info)
								<br/>
								<h5 class="titleLevel5">@(i + 1).@(getDiagnose2Index(i)).2.1 Logistic Regression</h5>
								<p class="paragraph">
									Results of Logistic Regression Model are shown below:
								</p>
								<p class="paragraph">
									Results of modeling are shown in file folder
									<a target="_blank" href="@(resultPath)Treatment/@(data.treats(i))/@(data.resultDatas(i).diagnoseDir)/02_Support_Vector_Machine/Diagnose_Model_Generation/Logistic_Regression">
										Logistic_Regression
									</a>
								</p>
								<p class="paragraph">
									Prediction result for each sample is shown in
									<a href="@(resultPath)Treatment/@(data.treats(i))/@(data.resultDatas(i).diagnoseDir)/02_Support_Vector_Machine/Diagnose_Model_Generation/Logistic_Regression/LR_Prediction.csv">
										LR_Prediction.csv
									</a>
									<a href="@(resultPath)Treatment/@(data.treats(i))/@(data.resultDatas(i).diagnoseDir)/02_Support_Vector_Machine/Diagnose_Model_Generation/Logistic_Regression" target="_blank"><span class="fa fa-folder-open"></span></a>
								</p>
								<p class="paragraph">
									Importance of each metabolite in model is shown in
									<a href="@(resultPath)Treatment/@(data.treats(i))/@(data.resultDatas(i).diagnoseDir)/02_Support_Vector_Machine/Diagnose_Model_Generation/Logistic_Regression/LR_VarImp.csv">
										LR_VarImp.csv
									</a>
									<a href="@(resultPath)Treatment/@(data.treats(i))/@(data.resultDatas(i).diagnoseDir)/02_Support_Vector_Machine/Diagnose_Model_Generation/Logistic_Regression" target="_blank"><span class="fa fa-folder-open"></span></a>
								</p>
								<p class="paragraph">
									ROC plot is shown in
									<a href="@(resultPath)Treatment/@(data.treats(i))/@(data.resultDatas(i).diagnoseDir)/02_Support_Vector_Machine/Diagnose_Model_Generation/Logistic_Regression/ROC_Curve.pdf" target="_blank">
										ROC_Curve.pdf
									</a>
									<a href="@(resultPath)Treatment/@(data.treats(i))/@(data.resultDatas(i).diagnoseDir)/02_Support_Vector_Machine/Diagnose_Model_Generation/Logistic_Regression" target="_blank"><span class="fa fa-folder-open"></span></a>
								</p>
								<p class="paragraph">
									PR curve is shown in
									<a href="@(resultPath)Treatment/@(data.treats(i))/@(data.resultDatas(i).diagnoseDir)/02_Support_Vector_Machine/Diagnose_Model_Generation/Logistic_Regression/PR_Curve.pdf" target="_blank">
										PR_Curve.pdf
									</a>
									<a href="@(resultPath)Treatment/@(data.treats(i))/@(data.resultDatas(i).diagnoseDir)/02_Support_Vector_Machine/Diagnose_Model_Generation/Logistic_Regression" target="_blank"><span class="fa fa-folder-open"></span></a>
								</p>
							</div>

							<div id="page" class="newPage">
								@user.report.pdf.pageHeader(path, data, info)
								<br/>
								<h5 class="titleLevel5">@(i + 1).@(getDiagnose2Index(i)).2.2 Random Forest</h5>
								<p class="paragraph">
									Results of Random Forest Model are shown below:
								</p>
								<p class="paragraph">
									Results of modeling are shown in file folder
									<a target="_blank" href="@(resultPath)Treatment/@(data.treats(i))/@(data.resultDatas(i).diagnoseDir)/02_Support_Vector_Machine/Diagnose_Model_Generation/Random_Forest">
										Random_Forest
									</a>
								</p>
								<p class="paragraph">
									Prediction result for each sample is shown in
									<a href="@(resultPath)Treatment/@(data.treats(i))/@(data.resultDatas(i).diagnoseDir)/02_Support_Vector_Machine/Diagnose_Model_Generation/Random_Forest/RF_Prediction.csv">
										RF_Prediction.csv
									</a>
									<a href="@(resultPath)Treatment/@(data.treats(i))/@(data.resultDatas(i).diagnoseDir)/02_Support_Vector_Machine/Diagnose_Model_Generation/Random_Forest" target="_blank"><span class="fa fa-folder-open"></span></a>

								</p>
								<p class="paragraph">
									Importance of each metabolite in model is shown in
									<a href="@(resultPath)Treatment/@(data.treats(i))/@(data.resultDatas(i).diagnoseDir)/02_Support_Vector_Machine/Diagnose_Model_Generation/Random_Forest/RF_VarImp.csv">
										RF_VarImp.csv
									</a>
									<a href="@(resultPath)Treatment/@(data.treats(i))/@(data.resultDatas(i).diagnoseDir)/02_Support_Vector_Machine/Diagnose_Model_Generation/Random_Forest" target="_blank"><span class="fa fa-folder-open"></span></a>
								</p>
								<p class="paragraph">
									ROC plot is shown in
									<a href="@(resultPath)Treatment/@(data.treats(i))/@(data.resultDatas(i).diagnoseDir)/02_Support_Vector_Machine/Diagnose_Model_Generation/Random_Forest/ROC_Curve.pdf" target="_blank">
										ROC_Curve.pdf
									</a>
									<a href="@(resultPath)Treatment/@(data.treats(i))/@(data.resultDatas(i).diagnoseDir)/02_Support_Vector_Machine/Diagnose_Model_Generation/Random_Forest" target="_blank"><span class="fa fa-folder-open"></span></a>

								</p>
								<p class="paragraph">
									PR curve is shown in
									<a href="@(resultPath)Treatment/@(data.treats(i))/@(data.resultDatas(i).diagnoseDir)/02_Support_Vector_Machine/Diagnose_Model_Generation/Random_Forest/PR_Curve.pdf" target="_blank">
										PR_Curve.pdf
									</a>
									<a href="@(resultPath)Treatment/@(data.treats(i))/@(data.resultDatas(i).diagnoseDir)/02_Support_Vector_Machine/Diagnose_Model_Generation/Random_Forest" target="_blank"><span class="fa fa-folder-open"></span></a>
								</p>
							</div>

							<div id="page" class="newPage">
								@user.report.pdf.pageHeader(path, data, info)
								<br/>
								<h5 class="titleLevel5">@(i + 1).@(getDiagnose2Index(i)).2.3 Gradient Boosting</h5>

								<p class="paragraph">
									Results of Gradient Boosting Model are shown below:
								</p>
								<p class="paragraph">
									Results of modeling are shown in file folder
									<a target="_blank" href="@(resultPath)Treatment/@(data.treats(i))/@(data.resultDatas(i).diagnoseDir)/02_Support_Vector_Machine/Diagnose_Model_Generation/Gradient_Boosting">
										Gradient_Boosting
									</a>
								</p>
								<p class="paragraph">
									Prediction result for each sample is shown in
									<a href="@(resultPath)Treatment/@(data.treats(i))/@(data.resultDatas(i).diagnoseDir)/02_Support_Vector_Machine/Diagnose_Model_Generation/Gradient_Boosting/GB_Prediction.csv">
										GB_Prediction.csv
									</a>
									<a href="@(resultPath)Treatment/@(data.treats(i))/@(data.resultDatas(i).diagnoseDir)/02_Support_Vector_Machine/Diagnose_Model_Generation/Gradient_Boosting" target="_blank"><span class="fa fa-folder-open"></span></a>
								</p>
								<p class="paragraph">
									Importance of each metabolite in model is shown in
									<a href="@(resultPath)Treatment/@(data.treats(i))/@(data.resultDatas(i).diagnoseDir)/02_Support_Vector_Machine/Diagnose_Model_Generation/Gradient_Boosting/GB_VarImp.csv">
										GB_VarImp.csv
									</a>
									<a href="@(resultPath)Treatment/@(data.treats(i))/@(data.resultDatas(i).diagnoseDir)/02_Support_Vector_Machine/Diagnose_Model_Generation/Gradient_Boosting" target="_blank"><span class="fa fa-folder-open"></span></a>
								</p>
								<p class="paragraph">
									ROC plot is shown in
									<a href="@(resultPath)Treatment/@(data.treats(i))/@(data.resultDatas(i).diagnoseDir)/02_Support_Vector_Machine/Diagnose_Model_Generation/Gradient_Boosting/ROC_Curve.pdf" target="_blank">
										ROC_Curve.pdf
									</a>
									<a href="@(resultPath)Treatment/@(data.treats(i))/@(data.resultDatas(i).diagnoseDir)/02_Support_Vector_Machine/Diagnose_Model_Generation/Gradient_Boosting" target="_blank"><span class="fa fa-folder-open"></span></a>
								</p>
								<p class="paragraph">
									PR curve is shown in
									<a href="@(resultPath)Treatment/@(data.treats(i))/@(data.resultDatas(i).diagnoseDir)/02_Support_Vector_Machine/Diagnose_Model_Generation/Gradient_Boosting/PR_Curve.pdf" target="_blank">
										PR_Curve.pdf
									</a>
									<a href="@(resultPath)Treatment/@(data.treats(i))/@(data.resultDatas(i).diagnoseDir)/02_Support_Vector_Machine/Diagnose_Model_Generation/Gradient_Boosting" target="_blank"><span class="fa fa-folder-open"></span></a>
								</p>
							</div>

						} else {
							@user.reportEn.html.noResult()
						}

						<div id="page" class="newPage">
							@user.report.pdf.pageHeader(path, data, info)
							<br/>
							<h5 class="titleLevel4">@(i + 1).@(getDiagnose2Index(i)).3 Feature Selection by Boruta</h5>
							<p class="paragraph">
								Data result of feature selection by Boruta is shown in
								<a href="@(resultPath)Treatment/@(data.treats(i))/@(data.resultDatas(i).diagnoseDir)/03_Boruta/Decision_Info.csv">
									Decision_Info.csv
								</a>
								<a href="@(resultPath)Treatment/@(data.treats(i))/@(data.resultDatas(i).diagnoseDir)/03_Boruta" target="_blank"><span class="fa fa-folder-open"></span></a>
							</p>
							<p class="paragraph">
								Plot of feature selection result by Boruta is shown in Figure
							</p>
							<p class="paragraph">
								Veen plot of features selected by RF, SVM and Boruta is showning in
								<a href="@(resultPath)Treatment/@(data.treats(i))/@(data.resultDatas(i).diagnoseDir)/Venn_Plot.pdf" target="_blank">
									Venn_Plot.pdf
								</a>
								<a href="@(resultPath)Treatment/@(data.treats(i))/@(data.resultDatas(i).diagnoseDir)/03_Boruta" target="_blank"><span class="fa fa-folder-open"></span></a>
							</p>

							<div class="noInNewPage">
								<p class="name_table">
									Figure @(i + 1)-@getDiagnoseImageIndex(i, 2) Feature Importance calculated by Boruta
								</p>
								<p class="center">
									<img class="wid2" src="@(resultPath)Treatment/@(data.treats(i))/@(data.resultDatas(i).diagnoseDir)/03_Boruta/Decision_Boxplot.png"/>
								</p>
							</div>

							<p class="paragraph">
								Green box labeled as “Confirmed” in the plot above can serve as biomarker for subsequent modeling. The subsequent analysis including Logistic Regression, Random Forest and Gradient Boosting model are all based on these “Confirmed” metabolites in Boruta.
							</p>
						</div>

						@if(!data.configDatas(i).isMul) {
							<div id="page" class="newPage">
								@user.report.pdf.pageHeader(path, data, info)
								<br/>
								<h5 class="titleLevel5">@(i + 1).@(getDiagnose2Index(i)).3.1 Logistic Regression</h5>
								<p class="paragraph">
									Results of Logistic Regression Model are shown below:
								</p>
								<p class="paragraph">
									Results of modeling are shown in file folder
									<a target="_blank" href="@(resultPath)Treatment/@(data.treats(i))/@(data.resultDatas(i).diagnoseDir)/03_Boruta/Diagnose_Model_Generation/Logistic_Regression">
										Logistic_Regression
									</a>
								</p>
								<p class="paragraph">
									Prediction result for each sample is shown in
									<a href="@(resultPath)Treatment/@(data.treats(i))/@(data.resultDatas(i).diagnoseDir)/03_Boruta/Diagnose_Model_Generation/Logistic_Regression/LR_Prediction.csv">
										LR_Prediction.csv
									</a>
									<a href="@(resultPath)Treatment/@(data.treats(i))/@(data.resultDatas(i).diagnoseDir)/03_Boruta/Diagnose_Model_Generation/Logistic_Regression" target="_blank"><span class="fa fa-folder-open"></span></a>
								</p>
								<p class="paragraph">
									Importance of each metabolite in model is shown in
									<a href="@(resultPath)Treatment/@(data.treats(i))/@(data.resultDatas(i).diagnoseDir)/03_Boruta/Diagnose_Model_Generation/Logistic_Regression/LR_VarImp.csv">
										LR_VarImp.csv
									</a>
									<a href="@(resultPath)Treatment/@(data.treats(i))/@(data.resultDatas(i).diagnoseDir)/03_Boruta/Diagnose_Model_Generation/Logistic_Regression" target="_blank"><span class="fa fa-folder-open"></span></a>
								</p>
								<p class="paragraph">
									ROC plot is shown in
									<a href="@(resultPath)Treatment/@(data.treats(i))/@(data.resultDatas(i).diagnoseDir)/03_Boruta/Diagnose_Model_Generation/Logistic_Regression/ROC_Curve.pdf" target="_blank">
										ROC_Curve.pdf
									</a>
									<a href="@(resultPath)Treatment/@(data.treats(i))/@(data.resultDatas(i).diagnoseDir)/03_Boruta/Diagnose_Model_Generation/Logistic_Regression" target="_blank"><span class="fa fa-folder-open"></span></a>
								</p>
								<p class="paragraph">
									PR curve is shown in
									<a href="@(resultPath)Treatment/@(data.treats(i))/@(data.resultDatas(i).diagnoseDir)/03_Boruta/Diagnose_Model_Generation/Logistic_Regression/PR_Curve.pdf" target="_blank">
										PR_Curve.pdf
									</a>
									<a href="@(resultPath)Treatment/@(data.treats(i))/@(data.resultDatas(i).diagnoseDir)/03_Boruta/Diagnose_Model_Generation/Logistic_Regression" target="_blank"><span class="fa fa-folder-open"></span></a>
								</p>
							</div>

							<div id="page" class="newPage">
								@user.report.pdf.pageHeader(path, data, info)
								<br/>
								<h5 class="titleLevel5">@(i + 1).@(getDiagnose2Index(i)).3.2 Random Forest</h5>
								<p class="paragraph">
									Results of Random Forest Model are shown below:
								</p>
								<p class="paragraph">
									Results of modeling are shown in file folder
									<a target="_blank" href="@(resultPath)Treatment/@(data.treats(i))/@(data.resultDatas(i).diagnoseDir)/03_Boruta/Diagnose_Model_Generation/Random_Forest">
										Random_Forest
									</a>
								</p>
								<p class="paragraph">
									Prediction result for each sample is shown in
									<a href="@(resultPath)Treatment/@(data.treats(i))/@(data.resultDatas(i).diagnoseDir)/03_Boruta/Diagnose_Model_Generation/Random_Forest/RF_Prediction.csv">
										RF_Prediction.csv
									</a>
									<a href="@(resultPath)Treatment/@(data.treats(i))/@(data.resultDatas(i).diagnoseDir)/03_Boruta/Diagnose_Model_Generation/Random_Forest" target="_blank"><span class="fa fa-folder-open"></span></a>

								</p>
								<p class="paragraph">
									Importance of each metabolite in model is shown in
									<a href="@(resultPath)Treatment/@(data.treats(i))/@(data.resultDatas(i).diagnoseDir)/03_Boruta/Diagnose_Model_Generation/Random_Forest/RF_VarImp.csv">
										RF_VarImp.csv
									</a>
									<a href="@(resultPath)Treatment/@(data.treats(i))/@(data.resultDatas(i).diagnoseDir)/03_Boruta/Diagnose_Model_Generation/Random_Forest" target="_blank"><span class="fa fa-folder-open"></span></a>
								</p>
								<p class="paragraph">
									ROC plot is shown in
									<a href="@(resultPath)Treatment/@(data.treats(i))/@(data.resultDatas(i).diagnoseDir)/03_Boruta/Diagnose_Model_Generation/Random_Forest/ROC_Curve.pdf" target="_blank">
										ROC_Curve.pdf
									</a>
									<a href="@(resultPath)Treatment/@(data.treats(i))/@(data.resultDatas(i).diagnoseDir)/03_Boruta/Diagnose_Model_Generation/Random_Forest" target="_blank"><span class="fa fa-folder-open"></span></a>

								</p>
								<p class="paragraph">
									PR curve is shown in
									<a href="@(resultPath)Treatment/@(data.treats(i))/@(data.resultDatas(i).diagnoseDir)/03_Boruta/Diagnose_Model_Generation/Random_Forest/PR_Curve.pdf" target="_blank">
										PR_Curve.pdf
									</a>
									<a href="@(resultPath)Treatment/@(data.treats(i))/@(data.resultDatas(i).diagnoseDir)/03_Boruta/Diagnose_Model_Generation/Random_Forest" target="_blank"><span class="fa fa-folder-open"></span></a>
								</p>
							</div>

							<div id="page" class="newPage">
								@user.report.pdf.pageHeader(path, data, info)
								<br/>
								<h5 class="titleLevel5">@(i + 1).@(getDiagnose2Index(i)).3.3 Gradient Boosting</h5>

								<p class="paragraph">
									Results of Gradient Boosting Model are shown below:
								</p>
								<p class="paragraph">
									Results of modeling are shown in file folder
									<a target="_blank" href="@(resultPath)Treatment/@(data.treats(i))/@(data.resultDatas(i).diagnoseDir)/03_Boruta/Diagnose_Model_Generation/Gradient_Boosting">
										Gradient_Boosting
									</a>
								</p>
								<p class="paragraph">
									Prediction result for each sample is shown in
									<a href="@(resultPath)Treatment/@(data.treats(i))/@(data.resultDatas(i).diagnoseDir)/03_Boruta/Diagnose_Model_Generation/Gradient_Boosting/GB_Prediction.csv">
										GB_Prediction.csv
									</a>
									<a href="@(resultPath)Treatment/@(data.treats(i))/@(data.resultDatas(i).diagnoseDir)/03_Boruta/Diagnose_Model_Generation/Gradient_Boosting" target="_blank"><span class="fa fa-folder-open"></span></a>
								</p>
								<p class="paragraph">
									Importance of each metabolite in model is shown in
									<a href="@(resultPath)Treatment/@(data.treats(i))/@(data.resultDatas(i).diagnoseDir)/03_Boruta/Diagnose_Model_Generation/Gradient_Boosting/GB_VarImp.csv">
										GB_VarImp.csv
									</a>
									<a href="@(resultPath)Treatment/@(data.treats(i))/@(data.resultDatas(i).diagnoseDir)/03_Boruta/Diagnose_Model_Generation/Gradient_Boosting" target="_blank"><span class="fa fa-folder-open"></span></a>
								</p>
								<p class="paragraph">
									ROC plot is shown in
									<a href="@(resultPath)Treatment/@(data.treats(i))/@(data.resultDatas(i).diagnoseDir)/03_Boruta/Diagnose_Model_Generation/Gradient_Boosting/ROC_Curve.pdf" target="_blank">
										ROC_Curve.pdf
									</a>
									<a href="@(resultPath)Treatment/@(data.treats(i))/@(data.resultDatas(i).diagnoseDir)/03_Boruta/Diagnose_Model_Generation/Gradient_Boosting" target="_blank"><span class="fa fa-folder-open"></span></a>
								</p>
								<p class="paragraph">
									PR curve is shown in
									<a href="@(resultPath)Treatment/@(data.treats(i))/@(data.resultDatas(i).diagnoseDir)/03_Boruta/Diagnose_Model_Generation/Gradient_Boosting/PR_Curve.pdf" target="_blank">
										PR_Curve.pdf
									</a>
									<a href="@(resultPath)Treatment/@(data.treats(i))/@(data.resultDatas(i).diagnoseDir)/03_Boruta/Diagnose_Model_Generation/Gradient_Boosting" target="_blank"><span class="fa fa-folder-open"></span></a>
								</p>
							</div>

						} else {
							@user.reportEn.html.noResult()
						}

					}

				}

				@if(i == data.treats.size - 1) {
					<div class="doubleSep"></div>
				} else {
					<div class="singleSep"></div>
				}

			}
			@user.reportEn.pdf.summary(resultPath, getSummaryIndex.toString, path, info)

			@if(info.isHuiyun) {
				@user.report.pdf.huiyunIntro(path, getIntroIndex.toString, data, info)
			}
			@if(info.isMet) {
				@user.report.pdf.metIntro(path, getIntroIndex.toString, data, info)
			}
			@if(info.isHuiyunLab) {
				@user.report.pdf.huiyunLabIntro(path, getIntroIndex.toString, data, info)
			}
			@if(info.isLiuyuan) {
				@user.report.pdf.liuyuanIntro(path, getIntroIndex.toString, data, info)
			}


				<!----------------------------------------------- End -------------------------------------------->
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